Computer Department, Tianjin Ren'ai College, Tianjin, 301636, China.
School of Information Engineering, Inner Mongolia university of science and technology, Baotou, 014010, China.
Sci Rep. 2023 Mar 21;13(1):4617. doi: 10.1038/s41598-023-30741-6.
With the advent of the era of big data, privacy computing analyzes and calculates data on the premise of protecting data privacy, to achieve data 'available and invisible'. As an important branch of secure multi-party computation, the geometric problem can solve practical problems in the military, national defense, finance, life, and other fields, and has important research significance. In this paper, we study the similarity problem of geometric graphics. First, this paper proposes the adjacency matrix vector coding method of isomorphic graphics, and use the Paillier variant encryption cryptography to solve the problem of isomorphic graphics confidentiality under the semi-honest model. Using cryptography tools such as elliptic curve cryptosystem, zero-knowledge proof, and cut-choose method, this paper designs a graphic similarity security decision protocol that can resist malicious adversary attacks. The analysis shows that the protocol has high computational efficiency and has wide application value in terrain matching, mechanical parts, biomolecules, face recognition, and other fields.
随着大数据时代的到来，隐私计算在保护数据隐私的前提下对数据进行分析和计算，实现数据“可用不可见”。作为安全多方计算的重要分支，几何问题可以解决军事、国防、金融、生活等领域的实际问题，具有重要的研究意义。本文研究了几何图形的相似性问题。首先，本文提出了同构图形的邻接矩阵向量编码方法，并利用 Paillier 变体加密密码学在半诚实模型下解决同构图形保密性问题。利用椭圆曲线密码系统、零知识证明、切选方法等密码学工具，本文设计了一种能够抵抗恶意对手攻击的图形相似性安全决策协议。分析表明，该协议具有较高的计算效率，在地形匹配、机械零件、生物分子、人脸识别等领域具有广泛的应用价值。
